1 About

This report is a contribution to the Hampshire County Council Climate Change Expert Stakeholder Forum’s Data sub-group.

Code: https://github.com/dataknut/hampshire-ghg-emissions (mirrored from https://git.soton.ac.uk/SERG/hcc-engagement/hampshire-ghg-emissions)

Feedback: https://github.com/HCC-CCECF-DataGroup/hampshire-ghg-emissions/labels/v2

1.1 History

Version 2.0 - [updated to use 2023 DESNZ CO2e data]

1.2 License

This report is (c) University of Southampton and is published under the CC-BY-4.0 license. You may share, re-use or adapt for commercial or non-commercial purposes with citation.

1.3 Citation

If you wish to use any of the material in this report please cite as:

Anderson, Ben (2023) ‘Wider Hampshire’ GHG Emissions (v2.0): 2018/19 baselines and trends over time, University of Southampton: Southampton.

2 Introduction

This report estimates greenhouse gas (GHG) emissions from the ‘wider Hampshire’ area using:

estimates of total annual territorial-based CO2e (selected GHGs) emissions from 2005 onwards using the latest local authority district level data from BEIS/DESNZ. This data now includes CO2, CH4 and N2O estimates from 2005 onwards;
estimates of total annual territorial-based CO2e (all GHGs) emissions for 2018/19 using the CSE Impact tool dataset;
estimates of total annual consumption-based CO2e (all GHGs) emissions for 2018/19 using the CSE Impact tool dataset.

Note that not all of the six GHGs of concern are covered by these datasets:

Carbon dioxide (CO2) - all datasets
Methane (CH4) - all datasets
Nitrous oxide (N2O) - all datasets
Hydrofluorocarbons (HFCs) - CSE Impact tool dataset only
Perfluorocarbons (PFCs) - CSE Impact tool dataset only
Sulphur hexafluoride (SF6) - CSE Impact tool dataset only

The analysis is carried out for the ‘Wider Hampshire’ area as defined in the map below (see Figure 2.1). This area includes all 14 local authorities in Hampshire including the unitary authorities of Portsmouth, Southampton and the Isle of Wight. Note that this differs from the baseline estimated by The Carbon Trust for the Hampshire County Council Climate Change Strategy which excluded the unitary authorities of Portsmouth, Southampton and the Isle of Wight.

Figure 2.1: Local authorities defining ‘Wider Hampshire’

3 Carbon Trust estimates

As background to the Hampshire County Council Climate Change Strategy, the Carbon Trust was asked to establish baseline emissions for the County excluding Southampton, Portsmouth and Isle of Wight. This baseline was converted to the proportion of emissions from different energy sources and reported as a trend plot on p14 of the Strategy as shown below. This highlighted that the main components of emissions were:

Industry & Commercial (~ 39%)
Transport (~ 37%)
Residential energy use (~ 24%).

Total kT CO2e baseline values were not included in this report.

Hampshire emissions (CarbonTrust, 2020)

However the HCC Climate Change Strategic Framework of Programmes which lays out the estimated Total kT CO2e and % reduction for a range of proposed actions, enables the following baseline values to be imputed:

Industry & Commercial emissions = 3,278 kT CO2
Transport emissions = 3,157 kT CO2
Residential emissions = 2,011 kT CO2

Using the proportion values in the figure above, this gives a total of 8,446 kT CO2 for the 11 districts.

4 DESNZ: Territorial-based selected GHG emissions (2005 to current)

These official local authority/district level DESNZ National Statistics use the end-user territorial emissions method (“meaning CO2e emissions that occur within the UK’s borders”). As a result international aviation and shipping are excluded from these estimates.

The GHGs included are:

Note that flourinated gases are therefore currently excluded.

Note also that:

“The end user basis for reporting emissions has been chosen for this dataset because it accounts for the emissions from energy use at the local level and does not penalise local areas for emissions from the production of energy which is then ‘exported’ to and used in other areas.” (technical report, p8)

DESNZ have produced a useful mapping tool which can be used to compare the spatial distribution of different emissions sources at district level.

The following code loads the data and reports basic checks. A full data description can be found in Section 10.1.

## Number of emissions categories (all local authorities): 32

## Number of local authorities (all): 377

Table 4.1: Number of local authorities per UK nation (unalocated = large electricity users/unallocated consumption/unkown location)
Country	N local authorities
England	309
Northern Ireland	11
Scotland	32
Unallocated	3
Wales	22

## Number of emissions categories (Hampshire local authorities): 31

## Number of local authorities (Hampshire local authorities): 14

Table 4.1: Wider Hampshire local authorities and data availability
Local Authority	Local Authority Code	N years of data	N emissions categories
Basingstoke and Deane	E07000084	17	31
East Hampshire	E07000085	17	30
Eastleigh	E07000086	17	30
Fareham	E07000087	17	30
Gosport	E07000088	17	29
Hart	E07000089	17	31
Havant	E07000090	17	30
Isle of Wight	E06000046	17	29
New Forest	E07000091	17	30
Portsmouth	E06000044	17	30
Rushmoor	E07000092	17	30
Southampton	E06000045	17	31
Test Valley	E07000093	17	31
Winchester	E07000094	17	30

4.1 Trends over time

Figure 4.1 shows trends over the period 2005 to 2019 for the CO2e emissions sources in the data. Overall there has been a clear reduction in emissions over the time period. The categories have been colour-coded so that related categories have similar colours in the palette.

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Figure 4.1: CO2e emissions by category (Hampshire)

Figure 4.2 shows trends over time for these categories using a line plot to make it easier to see which categories have declined. This makes the recent trends in the reduction of emissions from the increasingly decarbonised electricity grid clearly visible. There has also been a slight decline in emissions due to domestic gas use but few other sources show substantial change except for ‘large industrial installations’.

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Figure 4.2: CO2e emissions by category (Hampshire)

Figure 4.3 shows an interactive version of the same plot. Hovering over specific lines is useful for identifying the sources.

Figure 4.3: CO2e emissions by category (Hampshire)

4.1.1 Biogenic Net-Zero

It has been suggested that carbon sequestration through land-use and land-use change should be primarily used to offset ‘fast carbon cycle’ agricultural emissions rather than to offset (and thus enable) the continued burning of ‘slow carbon cycle’ fossil fuels. Figure 4.4 shows how close Hampshire is to net-zero biogenic emissions under the definitions included in the plot. Note that this excludes emissions from Agricultural gas and electricity use which are assumed to be from the burning of fossil fuels and thus part of the slow carbon cycle.

Figure 4.4: How close is Hampshire to biogenic Net-Zero?

In the most recent year, Hampshire had net biogenic emissions using the categories defined in the plot of 135 kT CO2e (negative emissions are 80 % of gross emissions). This value is positive, so emissions are larger than the level of sequestration (carbon capture). In this sense Hampshire is not yet biogenic net-zero.

4.2 2019 baseline

Table 4.2 shows the total CO2e emissions under this method for 2019 for all 14 districts.

Table 4.2: CO2e emissions (kT, 2019)
Total kT CO2e
9,409.2

## Total emissions for 2019: 9409 kT CO2e

## Total emissions deemed to be 'within the scope of influence of LAs' for 2019: 7623 kT CO2

Note that the total emissions deemed to be ‘within the scope of influence of LAs’ for 2019 is 0 kT CO2e. Categories deemed by DESNZ to be outside local authorities’ scope of influence in this data are:

all forms of land-use, land-use change and forestry
Transport: (Motorways)
Transport: Diesel Railways

Table 4.3 shows the total emissions for 2019 ordered by magnitude Figure 4.5 shows the data as a bar plot ordered by value. The largest emissions sources under this method are clearly visible (domestic gas, transport and domestic electricity).

Table 4.3: CO2e emissions sorted by magnitude (Hampshire, 2019)
Source	Total kT CO2e	% of gross
Domestic Gas	1,711.4	16.3
Transport: (A roads)	1,586.7	15.1
Transport: (Minor roads)	1,289.1	12.3
Transport: (Motorways)	992.3	9.5
Domestic Electricity	711.0	6.8
Industry 'Other'	451.1	4.3
Industry Electricity	402.0	3.8
Commercial Electricity	367.2	3.5
Agriculture Livestock	298.3	2.8
Industry Gas	275.9	2.6
Domestic 'Other'	257.8	2.5
Waste: Landfill	249.1	2.4
Public Sector Gas	244.7	2.3
Public Sector Electricity	180.2	1.7
Waste: other	177.2	1.7
Agriculture Soils	148.0	1.4
Commercial Gas	134.4	1.3
LULUCF Net Emissions: Cropland	108.6	1.0
Agriculture 'Other'	84.9	0.8
Industry: Large Industrial Installations	80.7	0.8
LULUCF Net Emissions: Settlements	66.5	0.6
Transport: Diesel Railways	42.4	0.4
Transport: other	34.7	0.3
Agriculture Electricity	33.8	0.3
Commercial 'Other'	11.2	0.1
Agriculture Gas	7.3	0.1
Public Sector 'Other'	4.5	0.0
LULUCF Net Emissions: Indirect N2O	2.0	0.0
LULUCF Net Emissions: Wetlands	0.0	0.0
LULUCF Net Emissions: Grassland	-67.4	-0.6
LULUCF Net Emissions: Forest land	-476.5	-4.5

Figure 4.5: CO2e emissions by category (Hampshire, 2019 ordered by emissions value)

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Figure 4.6 shows a cumulative emissions plot for the DESNZ 2019 data ordered by the emissions source’s magnitude. The largest increments are therefore due to domestic gas use and various forms of transport. The plot uses vertical lines to show the sources which comprise 50%, 75% and 90% of the total emissions. The plot curls due to the source categories with negative emissions such that the final point represents the total ‘net’ emissions.

Figure 4.6: Plot of cumulative emissions (DESNZ, 2019)

Thus, if we focus on territorial CO2e only then 75% of emissions are due to:

Domestic gas: 1,711 kT (18 %));
Transport (Motorways, A roads and minor roads combined): 3,868 kT (Total: 41 %);
Domestic electricity: 711 kT (8 %))

Taken together the domestic (residential) emissions comprise 26 % of the estimated total.

Negative CO2 emissions (sequestration) sources are:

Forest: -476 kT
Grassland: -67 kT - note that this does not include methane emissions from grazing livestock nor N2O emissions from waste
Wetlands: 0.029 kT - this is perhaps surprisingly small given the coastal nature of the County and the existence of a number of wetland habitats. it may be worth investigating the underlying data to confirm.

As Figure 4.6 showed, these levels of sequestration currently provide a negligible offset to the overall emissions. Note also that cropland was a net emitter at 109 kT.

Figure 4.2 showed that the only emissions sources showing substantial decreases over time have been electricity due to grid decarbonisation and (potentially) reductions in some industrial activity as well as the use of ‘Other fuels’ by industry. Although emissions from domestic gas use have also fallen over time they appear to have stabilised since 2014. Perhaps of most concern given their dominant contribution however is the relative stability of road transport emissions over the 2005 - 2019 period.

4.3 Latest data (2021)

Table 4.4: CO2e emissions sorted by magnitude (Hampshire, 2021)
Source	Total kT CO2e	% of gross
Domestic Gas	1,771.4	17.8
Transport: (A roads)	1,362.9	13.7
Transport: (Minor roads)	1,104.7	11.1
Transport: (Motorways)	868.4	8.7
Domestic Electricity	696.3	7.0
Industry 'Other'	481.5	4.8
Industry Electricity	371.4	3.7
Industry Gas	335.0	3.4
Commercial Electricity	314.1	3.2
Agriculture Livestock	273.2	2.7
Public Sector Gas	260.6	2.6
Domestic 'Other'	252.9	2.5
Waste: Landfill	204.8	2.1
Waste: other	197.1	2.0
Public Sector Electricity	163.1	1.6
Commercial Gas	137.2	1.4
Agriculture Soils	135.0	1.4
LULUCF Net Emissions: Cropland	110.8	1.1
Agriculture 'Other'	95.4	1.0
Industry: Large Industrial Installations	71.7	0.7
LULUCF Net Emissions: Settlements	60.3	0.6
Transport: Diesel Railways	36.2	0.4
Agriculture Electricity	29.3	0.3
Transport: other	26.9	0.3
Agriculture Gas	22.1	0.2
Commercial 'Other'	7.2	0.1
Public Sector 'Other'	2.7	0.0
LULUCF Net Emissions: Indirect N2O	2.0	0.0
LULUCF Net Emissions: Wetlands	0.0	0.0
LULUCF Net Emissions: Grassland	-70.9	-0.7
LULUCF Net Emissions: Forest land	-471.0	-4.7

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5 CSE: Territorial-based all GHG emissions (2018/19 data)

The first of the CSE datasets estimates emissions under the territorial method but including international aviation and shipping and includes all GHG emissions - carbon dioxide, methane, nitrous oxide and fluorinated gases. As the non-CO2 gases have different warming potentials compared to CO2, emissions are reported in terms of CO2e (carbon dioxide equivalent) rather than simply in terms of kT of gas emitted. The sum of kT CO2e for each source therefore represents the total contribution of all of the emissions to climate warming allowing for their different warming potentials.

The inclusion of GHGs other than just CO2 means that identical categories in the CSE data will most likely have higher emissions estimates than the original DESNZ equivalent which only accounted for CO2. As an example, Transport emissions are based on the DESNZ CO2 Transport emissions in the DESNZ pre 2020 data (no GHGs other than CO2) but were “adjusted to account for [additional] non-CO2 greenhouse gas emissions”. This is explained in detail in the CSE methodology paper:

“Total CO2e emissions have been estimated for most sectors by comparison of CO2, N2O and CH4 emission factors for the most prevalent fuel type in the sector and factoring the CO2 emissions accordingly. The exceptions are other transport and LULUCF due to the diverse nature of emission sources; in these cases the CO2 figures have been used as-is.” (p14)

For aviation and shipping:

“National emissions data from these sources are reported by the NAEI, and have been apportioned on a population basis.” (p15)

Finally, fluorinated gases (F-gases):

“are apportioned commensurate with non-domestic electricity emissions, as systems utilising such gases are most prevalent in non-domestic buildings and electrically powered equipment).” (p15)

The following code loads the data and reports basic checks. A full data description can be found in Section 10.2.

## Number of emissions categories: 20

## Number of districts: 14

## Total emissions check: 12110 kT CO2e

5.1 2019 baseline

Table 5.1 shows the total emissions for 2019. This is Inf % increase from the DESNZ figure.

Table 5.1: CSE territorial emissions (Hampshire, 2019)
Total kT CO2e
12,109.7

Table 5.2 shows the total emissions for 2019 by category. Figure 5.1 shows the data as a bar plot. Note that some of the categories do not exactly match those used in the DESNZ data but the colour palettes have been kept as similar as possible.

Ignore the (t CO2e) in the table and plot labels - both the table and plot show kT for easy comparison (labels to be fixed).

Table 5.2: CSE all territorial emissions by category (Hampshire, 2019)
variable	Total kT CO2e	% of gross
Housing - Mains gas (t CO2e)	1,657.5	12.8
Housing - Electricity (t CO2e)	841.3	6.5
Housing - Oil (t CO2e)	294.0	2.3
Housing - LPG (t CO2e)	38.0	0.3
Housing - Biomass (t CO2e)	8.0	0.1
Housing - Coal (t CO2e)	11.0	0.1
Industrial and commercial - Electricity (t CO2e)	1,110.0	8.6
Industrial and commercial - Mains gas (t CO2e)	702.5	5.4
Industrial and commercial - Other Fuels (t CO2e)	443.4	3.4
Industrial and commercial - Large industrial consumers (t CO2e)	81.5	0.6
Agriculture - Fuel (t CO2e)	106.7	0.8
Agriculture - Livestock and crop-related emissions (t CO2e)	350.4	2.7
Aviation (t CO2e)	1,202.6	9.3
Shipping (t CO2e)	479.0	3.7
Diesel fuelled railways (t CO2e)	45.3	0.3
F-gases (t CO2e)	374.1	2.9
Road Transport (t CO2e)	4,054.6	31.3
Other Transport (t CO2e)	31.2	0.2
Waste management (t CO2e)	703.7	5.4
Land use, land-use change, and forestry (t CO2e)	-425.2	-3.3

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Figure 5.1: CSE all territorial emissions by category (Hampshire, 2019 ordered by emissions value)

Figure 5.2 shows a cumulative emissions plot for the CSE territorial data ordered by the emissions source’s magnitude. The largest increments are therefore due to personal transport, domestic gas use and aviation. The plot shows the sources which comprise 50%, 75% and 90% of the total emissions. The plot curls due to the source categories with negative emissions such that the final point represents the total ‘net’ emissions.

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Figure 5.2: Plot of cumulative emissions (DESNZ, 2019)

Thus, if we focus on CSE territorial all GHG emissions, 75% of emissions are due to:

Road transport: 4,055 T CO2e (33 % of total)
Housing (domestic) gas: 1,657 T CO2e (14 % of total)
Aviation: 1,203 T CO2e - flights and freight (10 % of total)
Industrial & commercial electricity: 1,110 T CO2e (9 % of total)
Domestic electricity: 841 T CO2e (7 % of total)

These figures draw attention to the significant emissions due to aviation which are not included in the DESNZ LA level data. They also draw attention to the level of all GHG emissions from waste management. Indeed, 102 % of the 29 % increase from the DESNZ figure comprises emissions from:

Aviation (1,203 kT CO2e - i.e. flights & freight - 10 % of total);
Waste management (704 kT CO2e - 6 % of total);
Shipping (479 kT CO2e - 4 % of total) and
F-Gases (374 kT CO2e - 3 % of total)

Note that under the CSE approach, Agriculture - Livestock and crop-related emissions amount to 350 T CO2e compared to the DESNZ value for Cropland at 109 T CO2e which gives some indication of the additional emissions due to methane (noting that fuel used for agriculture is already in a separate category under the CSE approach - see methodology, p15).

6 CSE: Consumption-based all GHG emissions (2018/19 data)

These are calculated under the consumption emissions method and include all greenhouse gas emissions. They are also therefore presented in kT CO2e.

The following code loads the data and reports basic checks. A full data description can be found in Section 10.3.

## Number of emissions categories: 15

## Number of districts: 14

## Total emissions check: 13633 kT CO2e

6.1 2019 baseline

Table 6.1 shows the total emissions for 2019.

Table 6.1: CSE consumption emissions (Hampshire, 2019)
Total kT CO2e
13,633.3

Table 6.2 shows the total emissions for 2019 by category. Figure 6.1 shows the data as a bar plot. Note that most of the categories do not exactly match those used in the DESNZ/CSE territorial-based data but again, the colour palettes have been kept as similar as possible.

The largest emissions sources under this method are clearly visible (purchased goods, services and food/diet and gas-use).

Ignore the (t CO2e) in the label - the plot shows kT for easy comparison (labels to be fixed).

Table 6.2: CSE all consumption emissions ordered by category (Hampshire, 2019)
Source	Total kT CO2e	% of gross
Consumption of goods and services - Purchase of goods (t CO2e)	2,623.4	19.2
Consumption of goods and services - Use of services (t CO2e)	1,194.7	8.8
Consumption of goods and services - Other consumption related emissions (t CO2e)	1,034.1	7.6
Food and diet - Meat and fish (t CO2e)	1,722.0	12.6
Food and diet - Other food and drink (t CO2e)	1,413.7	10.4
Housing - Mains gas (t CO2e)	1,657.5	12.2
Housing - Electricity (t CO2e)	841.3	6.2
Housing - Oil (t CO2e)	294.0	2.2
Housing - LPG (t CO2e)	38.0	0.3
Housing - Biomass (t CO2e)	8.0	0.1
Housing - Coal (t CO2e)	11.0	0.1
Travel - Flights (t CO2e)	969.8	7.1
Travel - Public transport (t CO2e)	399.2	2.9
Travel - Private transport (t CO2e)	1,378.2	10.1
Waste - Waste (t CO2e)	48.4	0.4

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Figure 6.1: CSE all territorial emissions ordered by category value (Hampshire, 2019 ordered by emissions value)

Figure 6.2 shows a cumulative emissions plot for the CSE territorial data ordered by the emissions source’s magnitude. The largest increments are therefore due to consumption of goods and services, food and diet (meat & fish) and mains gas use. The plot shows the sources which comprise 50%, 75% and 90% of the total emissions.

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Figure 6.2: Plot of cumulative emissions (DESNZ, 2019)

Thus, if we focus on CSE consumption-based emissions which include emissions ‘outsourced’ to other geographical areas (including overseas), 75% of emissions sources are due to:

Purchased goods: 2,623 kT CO2e ( 19 %)
Food and diet - meat & fish: 1,722 kT CO2e ( 13 %)
Domestic gas: 1,657 kT CO2e as before ( 12 %)
Food and diet - other: 1,414 kT CO2e ( 10 %)
Private transport:1,378 kT CO2e ( 10 %)
Use of services: 1,195 kT CO2e ( 9 %)

Emissions due to Flights (970 kT CO2e) are lower than the territorial based Aviation emissions values since emissions due to freight are included under ‘Goods and services’.

This approach to emissions accounting shows the extent to which the consumption of goods and services, diet and food as well as transport and domestic gas use dominate Hampshire’s ‘consumption’ emissions footprint.

7 District level total emissions by method

Table 7.1 and Figure 7.1 show the total emissions under each method and source per district. As expected, in all cases CSE territorial emissions are higher than DESNZ territorial emissions. Similarly, in most cases CSE consumption emissions are higher than territorial emissions except for Winchester, Test Valley, Basingstoke and Deane and New Forest. More detailed analysis of the underlying data would be required to understand the reasons for this.

Table 7.1: Totals per district by method and source (kT)
District	DESNZ territorial emissions (kt CO2, 2019)	CSE territorial emissions (kt CO2e)	CSE consumption emissions (kt CO2e)
Basingstoke and Deane	1,115.4	1,351.7	1,309.4
East Hampshire	641.4	854.1	994.4
Eastleigh	593.2	748.8	902.3
Fareham	498.2	638.5	799.9
Gosport	221.3	305.2	497.1
Hart	500.3	628.4	782.8
Havant	425.0	556.3	786.0
Isle of Wight	626.4	788.7	999.8
New Forest	989.0	1,389.7	1,352.9
Portsmouth	802.4	1,117.3	1,192.4
Rushmoor	383.1	471.9	624.9
Southampton	783.6	1,039.2	1,386.2
Test Valley	920.7	1,136.3	986.4
Winchester	909.2	1,083.8	1,018.7

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Figure 7.1: Total emissions per district by method

8 Discussion

Overall, the total GHG emissions for Hampshire in 2018/19 under different methodologies were found to be:

Carbon Trust analysis (11 districts excluding Portsmouth, Southampton and the Isle of Wight): 8,446 kT CO2
DESNZ territorial CO2e:
- 7,197 kT CO2e (11 districts excluding Portsmouth, Southampton and the Isle of Wight),
- 9,409 kT CO2e (14 districts including Portsmouth, Southampton and the Isle of Wight)
CSE territorial emissions (all GHG, all 14 districts): 12,110 kT CO2e - 29 % higher than the DESNZ total
CSE consumption emissions (all GHG, all 14 districts): 13,633 kT CO2e

Given that the Carbon Trust area excludes Portsmouth, Southampton and the Isle of Wight it is unclear why this total is similar to the ‘14 local authorities’ DESNZ data.

Which of these accounting methods we choose to focus on depends what we want to show and what we want to achieve. The same is true of the emissions subcategories. The DESNZ data gives a partial view on territorial emissions as it excludesaviation (flights & freight) and shipping. The CSE territorial emissions data includes these ‘missing’ emissions and so gives a much larger total. The CSE consumption emissions are (generally) larger still because they include emissions ‘off-shored’ by our consumption of goods and services produced outside the Hampshire area.

Table 8.1 compares the Carbon Trust, DESNZ and CSE data for 2018/19 to the extent that it is possible to do so from the data reported here.

Table 8.1: Comparing 2018/19 emissions baselines (values = kT CO2e or %)
Source	CarbonTrust	Carbon Trust %	DESNZ	DESNZ %	CSE Territorial	CSE Territorial %	CSE Consumption	CSE Consumption %
Residential	2,011	22.7	2,680.2	28.5	2,849.8	23.5	2,849.8	20.9
Transport	3,157	36.1	3,945.2	41.9	4,085.8	33.7	1,777.3	13.0
Industry & Commercial	3,278	38.8	1,722.6	18.3	2,337.4	19.3
Aviation					1,202.6	9.9	969.8	7.1
Consumption of goods & services							4,852.3	35.6
Food & diet							3,135.7	23.0
Other			1,061.2	11.3	1,634.1	13.5	48.4	0.4

The table shows that the two main policy foci of the Hampshire County Council Climate Change Strategy - Transport and Residential - contribute at least 30% of emissions irrespective of the emissions accounting method used.

The Carbon Trust estimate for Industrial & Commercial emissions for the ‘11 districts’ appears to be considerably larger than the comparable DESNZ ‘14 districts’ value. This may be due to the exclusion in the DESNZ data of single large power stations whose emissions are ‘shared’ across all grid electricity users, not just those in the relevant district. As a result the DESNZ proportions for Transport and Residential emissions are higher (77% combined) compared to 58% in the Carbon Trust estimates for 11 districts.

Although the ‘14 districts’ DESNZ and CSE (territorial) main categories are broadly similar in terms of kT CO2(e), the percentage contribution of Transport and Residential emissions are considerably lower (56%) for the CSE data. This is due to the inclusion of additional sources in the CSE data such as Aviation (10%, shown) shipping and F-gases as well as all GHG emissions (not just CO2) from transport, waste, agriculture, and others (see Table 5.2 for details). Collectively these represent over 20% of county-wide emissions under the CSE territorial methodology.

Finally, the CSE consumption emissions data demonstrates the significant contribution that consumption of services as well as food and diet make to our ‘extended’ emissions footprint if we consider the emissions we have effectively off-shored to other geographical areas. This method transfers all of the industrial/commercial emissions and a significant proportion of the Transport/Aviation emissions to ‘Good and services’ and ‘Food and diet’ (i.e. supply chain transportation and distribution). As a result emissions from homes and private transport comprise only 33% of the total under this approach, flights a further 7% while the total for consumption of goods and services & food is ~58%

9 Recommendations and future work

Based on the preceding discussion, this report makes the following recommendations to HCC:

use all territorial emissions (e.g. due to aviation, shipping, F-gases) and all GHGs (i.e. carbon dioxide, methane, nitrous oxide) in the annual DESNZ district level emissions data as the benchmark for:
- estimation of baseline emissions;
- transparent modelling of the potential impact of HCC programmes on CO2 emissions;
- annual assessment of the district and county level emissions reduction progress;
- assessment of the impact of district and county level emissions reduction policies where feasible;
This will enable:
- robust baselining of emissions for all territorial GHGs, not just CO2;
- transparent modelling of the potential impact of HCC programmes on all territorial GHGs;
- effective monitoring of reductions in emissions of all territorial GHGs over time.
include a section in the HCC’s annual Climate Change Report which:
- reviews the mapping between current HCC programmes and the major emissions sources under each emissions accounting method;
- reviews the capability and capacity of County and District Authorities to influence the emissions sources for which no current programmes exist (c.f. the Committee on Climate Change’s recommendations as part of the 6th Carbon Budget and the more recent National Audit Office 2021 report on local government capabilities with respect to net zero in England);

Future work could:

work with DESNX to extend the local authority level GHG data to include fluorinated gases
use the DESNZ district level and (aggregated to) county level data to establish Science Based Targets for emissions reduction that align with or improve upon national ‘net-zero’ targets;
analyse the district level emissions to understand their distributions according to the different methodologies and hence inform district level prioritisation where this is not already in hand;
use the underlying LULUCF data to investigate the relatively low sequestration attributed to wetlands in the Hampshire area;
compare the results reported here with a similar analysis of the CREDS Place-Based Carbon Calculator consumption-based footprint data.

10 Appendix: Data

10.1 Data details: DESNZ

Original data (all districts)

Table 10.1: Data summary
Name	desnz_orig
Number of rows	523643
Number of columns	15
Key	NULL
_______________________
Column type frequency:
character	10
numeric	5
________________________
Group variables	None

Variable type: character

skim_variable	complete_rate	min	max	empty	n_unique
Country	1	5	16	0	5
Country Code	1	0	9	391	5
Region	1	5	24	0	13
Region Code	1	0	9	391	13
Second Tier Authority	1	0	28	391	152
Local Authority	1	4	54	0	377
Local Authority Code	1	9	11	0	376
LA GHG Sector	1	6	16	0	8
LA GHG Sub-sector	1	8	45	0	32
Greenhouse gas	1	3	3	0	3

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
Calendar Year	0	1	2012.99	4.90	2005.00	2009.00	2013.00	2017.00	2021.00	▇▆▆▆▇
Territorial emissions (kt CO2e)	0	1	16.74	95.02	-2892.14	0.04	0.49	4.66	10542.35	▁▇▁▁▁
CO2 emissions within the scope of influence of LAs (kt CO2e)	0	1	11.67	47.75	0.00	0.00	0.00	0.00	4027.53	▇▁▁▁▁
Mid-year Population (thousands)	391	1	172.28	116.21	2.21	100.09	136.68	211.72	1157.16	▇▂▁▁▁
Area (km2)	391	1	672.72	1653.91	3.15	98.35	279.33	680.08	26473.95	▇▁▁▁▁

10.2 Data details: CSE territorial

Original data (all districts)

Table 10.2: Data summary
Name	cse_terr_orig
Number of rows	331
Number of columns	23
Key	NULL
_______________________
Column type frequency:
character	2
numeric	21
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
id	0	1	9	9	0	331	0
name	0	1	4	35	0	331	0

Variable type: numeric

skim_variable	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
Housing - Mains gas (t CO2e)	1	190852.62	182673.33	0.00	97220.00	131038.45	223354.21	1385272.76	▇▁▁▁▁
Housing - Electricity (t CO2e)	1	86663.13	83524.18	1943.34	44655.72	63196.10	93121.88	663982.08	▇▁▁▁▁
Housing - Oil (t CO2e)	1	37606.39	69741.81	1.04	714.59	8789.51	48160.27	441375.15	▇▁▁▁▁
Housing - LPG (t CO2e)	1	4167.07	7371.96	0.00	469.25	1778.23	4239.50	61245.83	▇▁▁▁▁
Housing - Biomass (t CO2e)	1	771.86	1168.18	0.52	159.88	405.37	853.88	8950.32	▇▁▁▁▁
Housing - Coal (t CO2e)	1	1829.39	2952.05	0.00	427.02	845.21	1835.48	20794.73	▇▁▁▁▁
Industrial and commercial - Electricity (t CO2e)	1	132300.07	137891.68	2252.58	59765.86	86400.95	141105.07	923959.45	▇▁▁▁▁
Industrial and commercial - Mains gas (t CO2e)	1	113795.30	125630.61	0.00	42721.85	70456.50	130151.33	858852.28	▇▁▁▁▁
Industrial and commercial - Other Fuels (t CO2e)	1	53872.07	68865.42	1180.35	19306.49	33291.08	54312.41	475748.40	▇▁▁▁▁
Industrial and commercial - Large industrial consumers (t CO2e)	1	73703.57	409783.50	0.00	20.27	551.86	7433.72	6255114.95	▇▁▁▁▁
Power generation (t CO2e)	1	202476.76	820528.91	0.09	7.46	1783.81	13920.26	8217271.92	▇▁▁▁▁
Agriculture - Fuel (t CO2e)	1	16214.05	31376.01	19.35	1050.88	5662.08	17396.81	263250.12	▇▁▁▁▁
Agriculture - Livestock and crop-related emissions (t CO2e)	1	94318.64	209795.51	0.00	2268.33	20513.89	80007.64	1837654.01	▇▁▁▁▁
Aviation (t CO2e)	1	130491.98	134944.30	1357.78	62146.89	85907.73	154781.14	1118247.31	▇▁▁▁▁
Shipping (t CO2e)	1	51973.77	53747.08	540.79	24752.54	34216.27	61647.92	445387.71	▇▁▁▁▁
Diesel fuelled railways (t CO2e)	1	6482.85	9255.80	0.00	786.59	2905.88	7627.29	66721.19	▇▁▁▁▁
F-gases (t CO2e)	1	44589.47	46474.02	759.20	20143.06	29119.96	47557.04	311404.67	▇▁▁▁▁
Road Transport (t CO2e)	1	418242.72	490108.99	491.38	181517.18	295469.30	440058.82	4070305.68	▇▁▁▁▁
Other Transport (t CO2e)	1	7998.78	14329.64	194.29	1348.54	2844.33	8448.24	118796.62	▇▁▁▁▁
Waste management (t CO2e)	1	87630.55	118715.34	47.04	21207.78	45799.40	93602.67	811864.78	▇▁▁▁▁
Land use, land-use change, and forestry (t CO2e)	1	-21778.97	79199.08	-1114266.33	-22216.81	-5665.84	-1378.72	290789.88	▁▁▁▇▁

10.3 Data details: CSE consumption

Original data (all districts)

Table 10.3: Data summary
Name	cse_cons_orig
Number of rows	331
Number of columns	17
Key	NULL
_______________________
Column type frequency:
character	2
numeric	15
________________________
Group variables	None

Variable type: character

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
id	0	1	9	9	0	331	0
name	0	1	4	35	0	331	0

Variable type: numeric

skim_variable	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
Consumption of goods and services - Purchase of goods (t CO2e)	1	268862.96	254028.37	3253.64	137135.19	187813.51	297865.53	2009457.74	▇▁▁▁▁
Consumption of goods and services - Use of services (t CO2e)	1	122686.78	115963.99	1703.23	62807.03	83275.82	138173.10	916269.26	▇▁▁▁▁
Consumption of goods and services - Other consumption related emissions (t CO2e)	1	103039.49	98010.77	680.97	53703.24	72993.60	112484.27	786593.11	▇▁▁▁▁
Food and diet - Meat and fish (t CO2e)	1	180030.07	169391.00	2258.79	89337.21	123557.75	206969.04	1335364.18	▇▁▁▁▁
Food and diet - Other food and drink (t CO2e)	1	146601.40	138141.41	1707.71	73927.36	101001.71	166610.40	1093305.47	▇▁▁▁▁
Housing - Mains gas (t CO2e)	1	190852.62	182673.33	0.00	97220.00	131038.45	223354.21	1385272.76	▇▁▁▁▁
Housing - Electricity (t CO2e)	1	86663.13	83524.18	1943.34	44655.72	63196.10	93121.88	663982.08	▇▁▁▁▁
Housing - Oil (t CO2e)	1	37606.39	69741.81	1.04	714.59	8789.51	48160.27	441375.15	▇▁▁▁▁
Housing - LPG (t CO2e)	1	4167.07	7371.96	0.00	469.25	1778.23	4239.50	61245.83	▇▁▁▁▁
Housing - Biomass (t CO2e)	1	771.86	1168.18	0.52	159.88	405.37	853.88	8950.32	▇▁▁▁▁
Housing - Coal (t CO2e)	1	1829.39	2952.05	0.00	427.02	845.21	1835.48	20794.73	▇▁▁▁▁
Travel - Flights (t CO2e)	1	99293.70	97880.76	1263.94	49836.38	70791.32	104950.66	755526.40	▇▁▁▁▁
Travel - Public transport (t CO2e)	1	42579.54	40346.20	650.93	21713.78	29766.72	46779.59	316474.05	▇▁▁▁▁
Travel - Private transport (t CO2e)	1	145632.98	140132.03	2106.17	75665.79	105668.52	151288.59	1113486.12	▇▁▁▁▁
Waste - Waste (t CO2e)	1	6970.62	9644.02	98.62	2610.51	4438.13	8138.54	107477.57	▇▁▁▁▁

11 Appendix: R environment

Analysis completed in 27.26 seconds ( 0.45 minutes) using knitr in RStudio with R version 4.3.1 (2023-06-16) running on x86_64-apple-darwin20.

11.1 R packages used

base R (R Core Team 2016)
bookdown (Xie 2016a)
data.table (Dowle et al. 2015)
flextable (Gohel 2021)
knitr (Xie 2016b)
rmarkdown (Allaire et al. 2018)
skimr [skimr]

Appendix: References

Allaire, JJ, Yihui Xie, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, Hadley Wickham, Joe Cheng, and Winston Chang. 2018. Rmarkdown: Dynamic Documents for r. https://CRAN.R-project.org/package=rmarkdown.

Dowle, M, A Srinivasan, T Short, S Lianoglou with contributions from R Saporta, and E Antonyan. 2015. Data.table: Extension of Data.frame. https://CRAN.R-project.org/package=data.table.

Gohel, David. 2021. Flextable: Functions for Tabular Reporting. https://CRAN.R-project.org/package=flextable.

R Core Team. 2016. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

Xie, Yihui. 2016a. Bookdown: Authoring Books and Technical Documents with R Markdown. Boca Raton, Florida: Chapman; Hall/CRC. https://github.com/rstudio/bookdown.

———. 2016b. Knitr: A General-Purpose Package for Dynamic Report Generation in r. https://CRAN.R-project.org/package=knitr.

‘Wider Hampshire’ GHG Emissions (v2.0)

2018/19 baselines and trends over time

Ben Anderson (b.anderson@soton.ac.uk, `@dataknut`)

Last run at: 2023-08-03 09:08:26.137825

1 About

1.1 History

1.2 License

1.3 Citation

2 Introduction

3 Carbon Trust estimates

4 DESNZ: Territorial-based selected GHG emissions (2005 to current)

4.1 Trends over time

4.1.1 Biogenic Net-Zero

4.2 2019 baseline

4.3 Latest data (2021)

5 CSE: Territorial-based all GHG emissions (2018/19 data)

5.1 2019 baseline

6 CSE: Consumption-based all GHG emissions (2018/19 data)

6.1 2019 baseline

7 District level total emissions by method

8 Discussion

9 Recommendations and future work

10 Appendix: Data

10.1 Data details: DESNZ

10.2 Data details: CSE territorial

10.3 Data details: CSE consumption

11 Appendix: R environment

11.1 R packages used

Appendix: References

‘Wider Hampshire’ GHG Emissions (v2.0)

2018/19 baselines and trends over time

Ben Anderson (b.anderson@soton.ac.uk, @dataknut)

Last run at: 2023-08-03 09:08:26.137825

1 About

1.1 History

1.2 License

1.3 Citation

2 Introduction

3 Carbon Trust estimates

4 DESNZ: Territorial-based selected GHG emissions (2005 to current)

4.1 Trends over time

4.1.1 Biogenic Net-Zero

4.2 2019 baseline

4.3 Latest data (2021)

5 CSE: Territorial-based all GHG emissions (2018/19 data)

5.1 2019 baseline

6 CSE: Consumption-based all GHG emissions (2018/19 data)

6.1 2019 baseline

7 District level total emissions by method

8 Discussion

9 Recommendations and future work

10 Appendix: Data

10.1 Data details: DESNZ

10.2 Data details: CSE territorial

10.3 Data details: CSE consumption

11 Appendix: R environment

11.1 R packages used

Appendix: References

Ben Anderson (b.anderson@soton.ac.uk, `@dataknut`)